AIMC Topic: Humans

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Using machine learning to determine the nationalities of the fastest 100-mile ultra-marathoners and identify top racing events.

PloS one
The present study intended to determine the nationality of the fastest 100-mile ultra-marathoners and the country/events where the fastest 100-mile races are held. A machine learning model based on the XG Boost algorithm was built to predict the runn...

Examining worry and secondary stressors on grief severity using machine learning.

Anxiety, stress, and coping
BACKGROUND & OBJECTIVES: Worry and loss-related secondary stressors appear to be important correlates of problematic grief responses. However, the relative importance of these variables in the context of established correlates of grief responding, ra...

Feasibility of Artificial Intelligence Powered Adverse Event Analysis: Using a Large Language Model to Analyze Microwave Ablation Malfunction Data.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Determine if a large language model (LLM, GPT-4) can label and consolidate and analyze interventional radiology (IR) microwave ablation device safety event data into meaningful summaries similar to humans. Microwave ablation safety data from Januar...

Machine learning identifies clusters of the normal adolescent spine based on sagittal balance.

Spine deformity
PURPOSE: This study applied a machine learning semi-supervised clustering approach to radiographs of adolescent sagittal spines from a single pediatric institution to identify patterns of sagittal alignment in the normal adolescent spine. We sought t...

Finding the Needle in the Haystack: Can Natural Language Processing of Students' Evaluations of Teachers Identify Teaching Concerns?

Journal of general internal medicine
BACKGROUND: Institutions rely on student evaluations of teaching (SET) to ascertain teaching quality. Manual review of narrative comments can identify faculty with teaching concerns but can be resource and time-intensive.

Ethics of Writing Personal Statements and Letters of Recommendations with Large Language Models.

ATS scholar
Large language models are becoming ubiquitous in the editing and generation of written content and are actively being explored for their use in medical education. The use of artificial intelligence (AI) engines to generate content in academic spaces ...

Learning the feature distribution similarities for online time series anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Identifying anomalies in multi-dimensional sequential data is crucial for ensuring optimal performance across various domains and in large-scale systems. Traditional contrastive methods utilize feature similarity between different features extracted ...

Prediction of 90 day readmission in heart failure with preserved ejection fraction by interpretable machine learning.

ESC heart failure
AIMS: Certain critical risk factors of heart failure with preserved ejection fraction (HFpEF) patients were significantly different from those of heart failure with reduced ejection fraction (HFrEF) patients, resulting in the limitations of existing ...

Artificial Intelligence-Based Classification of CT Images Using a Hybrid SpinalZFNet.

Interdisciplinary sciences, computational life sciences
The kidney is an abdominal organ in the human body that supports filtering excess water and waste from the blood. Kidney diseases generally occur due to changes in certain supplements, medical conditions, obesity, and diet, which causes kidney functi...